model cellular automata-markov chain for prediction of...

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Model Cellular Automata-Markov Chain For Prediction of Development and Land

Carrying Capacity of Settlement in Balikpapan City, East Kalimantan Province

Wahdini Safira, Astrid Damayanti, Tito Latif Indra, Muhammad Dimyati

Geography Departement, Mathematics and Natural Sciences Faculty, Universitas Indonesia

INSTRODUCTION

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CA-MC ModelLand Carrying Capacity of Settlement

Population Growth

Land Needs

LULC ChangesResearch Purpose

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Driving Factor

Height, slope, distance from the

road, river, and coastline

Data

Landsat imagery in 2008, 2014, and 2020.

Study Area

Located 116,50 BT- 117,00 BT and1,00 LS - 1,50 LS.

Study Area and Data

RESEARCH METHOD

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Calculate Land Carrying capacity

𝐷𝐷𝑃𝑚 = (𝐿𝑃𝑚/𝐽𝑃)/ 𝛼

Simulation Cellular Automata-Markov

Chain

Fuzzy overlay Driving factor

Image preprocessingand supervised classification

Calculate Population projection

𝑃𝑡= 𝑃0(1 + 𝑟)𝑡 with 𝑟 =𝑃𝑡𝑃0

1𝑡

− 1

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RESULT AND DISCUSSION - Settlement Development

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RESULT AND DISCUSSION – Prediction in 2032

RESULT AND DISCUSSION – Land Carrying Capacity

Based on land suitability

▪ DDPm = 8,45 m2/ capita.▪ DDPm >1, the carrying

capacity of settlementsis high

▪ Still able toaccommodate thesettlement increase

Based on RTRW

▪ DDPm = -0,64 m2/capita.▪ DDPm <1, the carrying

capacity of settlements islow

▪ Unable to accommodateresidents to settle.

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CONCLUSION

▪ Settlements aredeveloping rapidly

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▪ The carrying capacityof settlements basedon land suitability ishigh, whereas basedon RTRW is low▪ Develop in areas

with good physicalcondition

REFERENCES

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